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共 117 条记录，以下是31-40 订阅

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PD pattern recognition on Transmission Lines using Tree-Based Models 2

PD Pattern Recognition on Transmission Lines using Tree-Base...

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2nd ieee international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2020

作者： Venkatesh, D. Swankg, Eyuwankg S Valarmathi, R. Uma, R. Sri Sairam Engineering College Department of Computer Science Engineering Chennai India

ISBN: (纸本)9781728110844

Partial discharge (PD) is a dielectric breakdown phenomenon that is caused due to cracks or voids in the insulation of the transmission lines. If PD is left alone, then it may completely damage the power lines and even starts a fire. This paper provides a machine learning approach (Tree-Based models) using the VSB dataset to solve the problem. The Tree-Based models like Decision Tree, Random Forest, and Gradient Boosting machine were used to detect the PD patterns. The results of all three models have been recorded and analyzed based on the Evaluation Metrics. Decision Tree gave an accuracy of 92.5% whereas Random Forest and Gradient Boosting machine gave an accuracy of 94.8%. © 2020 ieee.

关键词： Electric lines

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Fake Currency Detection Using pattern recognition Algorithm 2

Fake Currency Detection Using Pattern Recognition Algorithm

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2nd ieee international conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Ananth, N.S Yoga Suba Lakshmi, S. Narmatha, B. Sundari, G. P.S.R Engineering College Electronics and Communication Engineering Tamilnadu Sivakasi India

ISBN: (纸本)9798350384277

The creation of numerous counterfeit banknotes in recent years has had a detrimental effect on society and resulted in significant losses. Thus, it is now imperative to establish a technique for identifying fake cash. To combat this problem, the article uses a pattern recognition algorithm to provide a strong solution for fake currency identification. The aim is to create a precise and effective system that can differentiate between real currency and fake notes. In order to examine and distinguish between the complex characteristics and security elements incorporated in real money notes, The method retrieves important visual properties, including watermarks, security threads, holograms, and other security aspects, by using sophisticated image processing algorithms. After that, a machine-learning model for categorization is trained using these features. The suggested solution incorporates a broad dataset of real and fake banknotes. It uses a diverse dataset of authentic and counterfeit notes to train a machine-learning model. The system's accuracy and efficiency are evaluated against real-world counterfeit samples, resulting in a high detection rate and a low false-positive rate. This technology enhances financial system security and integrity. The system's effectiveness, reliability, and adaptability make it a crucial tool in combating counterfeit currency, safeguarding economic stability, and promoting trust in financial transactions © 2024 ieee.

关键词： machine learning

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Applications of pattern recognition for Hyper Spectral Time Series Algorithm Detection 2

Applications of Pattern Recognition for Hyper Spectral Time ...

引用

2nd international conference on Artificial Intelligence and machine learning Applications, AIMLA 2024

作者： Srivastava, Manish Jamuna, K.V. Pandey, Arvind Kumar Vivekananda Global University Department of Electrical Engineering Jaipur India School of Sciences Department of Forensic Science Karnataka Bangalore India ARKA JAIN University Department of Computer Science & IT Jharkhand Jamshedpur India

ISBN: (纸本)9798350349221

Sample recognition is the system of changing complicated, multidimensional data into significant patterns that may be used for numerous analytical or predictive purposes. It's used to discover, classify, and discover styles within huge units of facts and is specifically beneficial while handling excessive-dimensional and hyper-spectral time series information. The application of pattern reputation for hyper spectral time collection set of rules detection is a rising area which has been used in a number of applications. This approach has been applied within the subject of remote sensing and environmental monitoring to detect various target gadgets or capabilities. It has also been used within the healthcare industry to discover unusual tissue inside medical snapshots. Moreover, this method is utilized in bioinformatics and system learning packages to locate subtle styles in massive datasets of medical or organic samples. In conclusion, the sample reputation for hyper spectral time collection algorithm detection is a precious device for its capacity to extract styles from excessive-dimensional information, allowing researchers to recognize the underlying relationships between variables in order to benefit new insights and broaden greater accurate fashions... © 2024 ieee.

关键词： pattern recognition

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Entity relationship extraction based on bi-channel neural network 2

Entity relationship extraction based on bi-channel neural ne...

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2nd international conference on machine learning, Big Data and Business Intelligence, MLBDBI 2020

作者： Cheng, Wenlong Xiong, Junqiao Wuhan Institute of Technology Institute for Pattern Recognition and Artificial Intelligence Wuhan China

ISBN: (纸本)9781728196381

It is of extremely important research value to identify the hidden relationship between the entities and extracted entities in this paper. Based on the two-channel convolutional neural network, the bi-directional long-short term memory network and multi-head attention mechanism have been added by this paper, and a relational extraction model of the two- channel neural network has been proposed. After the training of word vector, the resulting feature fusion is further classified, and finally the experimental verification is conducted on the SemEval-2010 Task 8 data set. The validation results have shown that this method has a good relationship extraction effect. © 2020 ieee.

关键词： Convolutional neural networks

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pattern recognition in Analog Wafermaps with Multiple Ensemble Approaches 2

Pattern Recognition in Analog Wafermaps with Multiple Ensemb...

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2nd international conference on Robotics, Electrical and Signal Processing Techniques, ICREST 2021

作者： Abdullah, Md. Rahman, Md. Habibur Akhter, Shamim International University of Business Agriculture and Technology Aisip Lab Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665415767

A wafer is a thin slice or substrate of semiconductors used for the fabrication of microelectronics devices. Thus, a large scale of precision is needed to make the microdevices work properly and to meet the requirements. Wafer test is an important step in wafer manufacturing to validate the activity of the microdevices and produces pictures of each wafer based on the electrical measurement of each of the devices on the wafer. Wafer shows different patterns while testing based on the requirement gap present on some of the devices on the wafer. To detect this error pattern manually is almost an impossible and time-consuming act. Therefore, we are presenting a wafer map pattern recognition system based on some ensemble approaches. Three (3) different ensemble including bagging, boosting, and voting approaches are implemented. Bagging performs relatively better than the others. © 2021 ieee.

关键词： machine learning

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Proceedings of 2nd ieee international conference on Computational Intelligence and Knowledge Economy, ICCIKE 2021

Proceedings of 2nd IEEE International Conference on Computat...

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2nd ieee international conference on Computational Intelligence and Knowledge Economy, ICCIKE 2021

ISBN: (纸本)9781665429214

The proceedings contain 106 papers. The topics discussed include: measuring human eye tolerance towards the digital typography sharpness on a high-density pixel computer screen: an indicative study;incentives or sanctions: an enforcement theory perspective to sustainable consumerism;smart hospital: automation of business processes in medical centers;an efficient SQL injection detection system using deep learning;a CNN-BiLSTM based approach for detection of SQL injection attacks;harnessing smart integration: blockchain-enabled B2C reverse supply chain;human gait analysis using machine learning: a review;global financial crisis in 21st century: a brief analysis of stock exchanges;logistics and IoT based survival strategies to facilitate supply chain engineering during pandemic;and a deep neural inferencing approach of assistive Philippine traffic light recognition: an augmented transfer learning approach.

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Hybrid Multidimensional Wavelet-Neuro-System and its learning Using Cross Entropy Cost Function in pattern recognition 2

Hybrid Multidimensional Wavelet-Neuro-System and its Learnin...

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2nd ieee international conference on Data Stream Mining and Processing (DSMP)

作者： Vynokurova, Olena Peleshko, Dmytro Borzov, Yuriy Oskerko, Semen Voloshyn, Viktor IT Step Univ Lvov Ukraine Lviv State Univ Life Safety Dept Project Management Informat Technol & Teleco Lvov Ukraine

ISBN: (纸本)9781538628744

In this paper, the hybrid multidimensional wavelet-neuro-system for pattern recognition tasks is proposed. Also learning algorithm for all its parameters (synaptic weights, the centers, and widths of wavelet activation functions) based on cross entropy cost function was proposed. The proposed system is characterized by high learning speed and high approximation properties in comparison with well-known approaches. The efficiency of the proposed approach has been justified based on different benchmarks and real data sets.

关键词： patterns recognition hybrid wavelet-neuro-system learning algorithm wavelet transform cross entropy cost function

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Real-time robotic hand control using hand gestures 2nd

Real-time robotic hand control using hand gestures

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2010 The 2nd international conference on machine learning and Computing, ICMLC 2010

作者： Raheja, Jagdish Lal Shyam, Radhey Kumar, Umesh Prasad, P. Bhanu Pilani - 333031 Rajasthan India

ISBN: (纸本)9780769539775

This paper presents a new approach for controlling robotic hand or an individual robot by merely showing hand gestures in front of a camera. With the help of this technique one can pose a hand gesture in the vision range of a robot and corresponding to this notation, desired action is performed by the robotic system. Simple video camera is used for computer vision, which helps in monitoring gesture presentation. This approach consists of four modules: (a) A real time hand gesture formation monitor and gesture capture, (b) feature extraction, (c) pattern matching for gesture recognition, (d) Command determination corresponding to shown gesture and performing action by robotic system. Real-time hand tracking technique is used for object detection in the range of vision. If a hand gesture is shown for one second, the camera captures the gesture. Object of interest is extracted from the background and the portion of hand, representing the gesture, is cropped out using the statistical property of hand. Extracted hand gesture is matched with the stored database of hand gestures using pattern matching. Corresponding to the matched gesture, action is performed by the robot. © 2010 ieee.

关键词： pattern matching

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A pattern Analysis-based Segmentation to Localize Early and Late Blight Disease Lesions in Digital Images of Plant Leaves

A Pattern Analysis-based Segmentation to Localize Early and ...

引用

ieee international conference on Signal and Image Processing Applications (ieee ICSIPA)

作者： Abdu, Aliyu Muhammad Mokji, Musa Mohd Sheikh, Usman Ullah Univ Technol Malaysia Sch Elect Engn Skudai 81310 Malaysia

ISBN: (纸本)9781728133775

This study reports a disease symptom classification algorithm using a proposed pattern recognition approach to individually localize early and late blight visual disease symptoms. The algorithm uses the pathological analogy hierarchy of the diseases to produce a novel homogeneous pattern localization, more informative to extract features that would be utilized for a machine learning system to classify the two diseases in digital photographs of vegetable plants. One of the most significant advantages of the proposed pattern analysis is localizing symptomatic and necrotic regions based on pathological disease analogy using soft computing, with which the pattern of each disease manifestation along the leaf surface can be tracked and quantified for characterization. In the 1st phase of the experiment, individual symptomatic (R-S), necrotic (R-N), and blurred (R-B, in-between healthy and symptomatic) regions were identified, segmented, and quantified. The 2nd phase focuses on the extraction of pattern features for classification and severity estimation with a machine learning classifier. The obtained results are encouraging, successfully localizing and quantifying individual disease lesions. This also indicates the enhanced applicability of the proposed approach discriminating the two diseases based on their dissimilarity. It is also envisaged that the algorithm can be extended to other plant disease symptoms. Moreover, it provides opportunities for early identification and detection of subtle changes in plant growth, disease stage, and severity estimation to assisting crop diagnostics in precision agriculture.

关键词： pattern analysis Computer vision Segmentation Plant disease lesion Plant disease detection

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To Decrease the Rate of Cyber Anomalies Using Intrusion Detection System with Feature Selection Approach 2

To Decrease the Rate of Cyber Anomalies Using Intrusion Dete...

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2nd international conference on Disruptive Technologies, ICDT 2024

作者： Tomar, Anshika Umrao, Sandhya Kumar, Dileep Noida Institute of Engineering and Technology India Noida Institute of Engineering and Technology India

ISBN: (纸本)9798350371055

This review provides a comprehensive survey of the current state of search engine access, highlighting their strengths, limitations, and changes over time. It evaluates the various options used in IDS, demonstrating their effectiveness in reducing the computational burden while increasing the accuracy of the suspicion. Also, this article explains the choice to combine machine learning, data mining and statistical methods in the features of the IDS framework.. It evaluates the impact of these processes on reducing vulnerabilities, improving detection rates, and adapting to changing cyber threats. © 2024 ieee.

关键词： Anomaly Detection Attack Detection Risk Management Classification Algorithms Cyber Anomalies Data Mining Feature Selection Information Security Intrusion Detection System machine learning Malware Detection Network Security Network Traffic Analysis pattern recognition Performance Evaluation Security Measures Threat Detection

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